Matching Items (79)
Description
Human breath is a concoction of thousands of compounds having in it a breath-print of physiological processes in the body. Though breath provides a non-invasive and easy to handle biological fluid, its analysis for clinical diagnosis is not very common. Partly the reason for this absence is unavailability of cost effective and convenient tools for such analysis. Scientific literature is full of novel sensor ideas but it is challenging to develop a working device, which are few. These challenges include trace level detection, presence of hundreds of interfering compounds, excessive humidity, different sampling regulations and personal variability. To meet these challenges as well as deliver a low cost solution, optical sensors based on specific colorimetric chemical reactions on mesoporous membranes have been developed. Sensor hardware utilizing cost effective and ubiquitously available light source (LED) and detector (webcam/photo diodes) has been developed and optimized for sensitive detection. Sample conditioning mouthpiece suitable for portable sensors is developed and integrated. The sensors are capable of communication with mobile phones realizing the idea of m-health for easy personal health monitoring in free living conditions. Nitric oxide and Acetone are chosen as analytes of interest. Nitric oxide levels in the breath correlate with lung inflammation which makes it useful for asthma management. Acetone levels increase during ketosis resulting from fat metabolism in the body. Monitoring breath acetone thus provides useful information to people with type1 diabetes, epileptic children on ketogenic diets and people following fitness plans for weight loss.
ContributorsPrabhakar, Amlendu (Author) / Tao, Nongjian (Thesis advisor) / Forzani, Erica (Committee member) / Lindsay, Stuart (Committee member) / Arizona State University (Publisher)
Created2013
Description
Surface plasmon resonance (SPR) has emerged as a popular technique for elucidating subtle signals from biological events in a label-free, high throughput environment. The efficacy of conventional SPR sensors, whose signals are mass-sensitive, diminishes rapidly with the size of the observed target molecules. The following work advances the current SPR sensor paradigm for the purpose of small molecule detection. The detection limits of two orthogonal components of SPR measurement are targeted: speed and sensitivity. In the context of this report, speed refers to the dynamic range of measured kinetic rate constants, while sensitivity refers to the target molecule mass limitation of conventional SPR measurement. A simple device for high-speed microfluidic delivery of liquid samples to a sensor surface is presented to address the temporal limitations of conventional SPR measurement. The time scale of buffer/sample switching is on the order of milliseconds, thereby minimizing the opportunity for sample plug dispersion. The high rates of mass transport to and from the central microfluidic sensing region allow for SPR-based kinetic analysis of binding events with dissociation rate constants (kd) up to 130 s-1. The required sample volume is only 1 μL, allowing for minimal sample consumption during high-speed kinetic binding measurement. Charge-based detection of small molecules is demonstrated by plasmonic-based electrochemical impedance microscopy (P-EIM). The dependence of surface plasmon resonance (SPR) on surface charge density is used to detect small molecules (60-120 Da) printed on a dextran-modified sensor surface. The SPR response to an applied ac potential is a function of the surface charge density. This optical signal is comprised of a dc and an ac component, and is measured with high spatial resolution. The amplitude and phase of local surface impedance is provided by the ac component. The phase signal of the small molecules is a function of their charge status, which is manipulated by the pH of a solution. This technique is used to detect and distinguish small molecules based on their charge status, thereby circumventing the mass limitation (~100 Da) of conventional SPR measurement.
ContributorsMacGriff, Christopher Assiff (Author) / Tao, Nongjian (Thesis advisor) / Wang, Shaopeng (Committee member) / LaBaer, Joshua (Committee member) / Chae, Junseok (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation proposes a miniature FIR filter that works at microwave frequencies, whose filter response can ideally be digitally programmed. Such a frequency agile device can find applications in cellular communications and wireless networking. The basic concept of the FIR filter utilizes a low loss acoustic waveguide of appropriate geometry that acts as a traveling wave tapped-delay line. The input RF signal is applied by an array of capacitive transducers at various locations on the acoustic waveguide at one end that excites waves of a propagating acoustic mode with varying spatial delays and amplitudes which interfere as they propagate. The output RF signal is picked up at the other end of the waveguide by another array of capacitive transducers. Tuning of the FIR filter coefficients is realized by controlling the DC voltage profile applied to the individual transducers which essentially shapes the overall filter response. Equivalent circuit modeling of the capacitive transducer, acoustic waveguide and transducer-line coupling is presented in this dissertation. A theoretical model for the filter is developed from a general theory of an array of transducers exciting a waveguide and is used to obtain a set of filter design equations. A MATLAB based circuit simulator is developed to simulate the filter responses. Design parameters and simulation results obtained for an example waveguide structure are presented and compared to the values estimated by the theoretical model. A waveguide structure utilizing the Rayleigh-like mode of a ridge is then introduced. A semi-analytical method to obtain propagating elastic modes of such a ridge waveguide etched in an anisotropic crystal is presented. Microfabrication of a filter based on ridges etched in single crystal Silicon is discussed along with details of the challenges faced. Finally, future work and a few alternative designs are presented that can have a better chance of success. Analysis and modeling work to this point has given a good understanding of the working principles, performance tradeoffs and fabrication pitfalls of the proposed device. With the appropriate acoustic waveguide structure, the proposed device could make it possible to realize miniature programmable FIR filters in the GHz range.
ContributorsGalinde, Ameya (Author) / Abbaspour-Tamijani, Abbas (Thesis advisor) / Chae, Junseok (Committee member) / Pan, George (Committee member) / Phillips, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
ABSTRACT This work seeks to develop a practical solution for short range ultrasonic communications and produce an integrated array of acoustic transmitters on a flexible substrate. This is done using flexible thin film transistor (TFT) and micro electromechanical systems (MEMS). The goal is to develop a flexible system capable of communicating in the ultrasonic frequency range at a distance of 10 - 100 meters. This requires a great deal of innovation on the part of the FDC team developing the TFT driving circuitry and the MEMS team adapting the technology for fabrication on a flexible substrate. The technologies required for this research are independently developed. The TFT development is driven primarily by research into flexible displays. The MEMS development is driving by research in biosensors and micro actuators. This project involves the integration of TFT flexible circuit capabilities with MEMS micro actuators in the novel area of flexible acoustic transmitter arrays. This thesis focuses on the design, testing and analysis of the circuit components required for this project.
ContributorsDaugherty, Robin (Author) / Allee, David R. (Thesis advisor) / Chae, Junseok (Thesis advisor) / Aberle, James T (Committee member) / Vasileska, Dragica (Committee member) / Arizona State University (Publisher)
Created2012
Description
High temperature CO2 perm-selective membranes offer potential for uses in various processes for CO2 separation. Recently, efforts are reported on fabrication of dense ceramic-carbonate dual-phase membranes. The membranes provide selective permeation to CO2 and exhibit high permeation flux at high temperature. Research on transport mechanism demonstrates that gas transport for ceramic-carbonate dual-phase membrane is rate limited by ion transport in ceramic support. Reducing membrane thickness proves effective to improve permeation flux. This dissertation reports strategy to prepare thin ceramic-carbonate dual-phase membranes to increase CO2 permeance. The work also presents characteristics and gas permeation properties of the membranes. Thin ceramic-carbonate dual-phase membrane was constructed with an asymmetric porous support consisting of a thin small-pore ionic conducting ceramic top-layer and a large pore base support. The base support must be carbonate non-wettable to ensure formation of supported dense, thin membrane. Macroporous yttria-stabilized zirconia (YSZ) layer was prepared on large pore Bi1.5Y0.3Sm0.2O3-δ (BYS) base support using suspension coating method. Thin YSZ-carbonate dual-phase membrane (d-YSZ/BYS) was prepared via direct infiltrating Li/Na/K carbonate mixtures into top YSZ layers. The thin membrane of 10 μm thick offered a CO2 flux 5-10 times higher than the thick dual-phase membranes. Ce0.8Sm0.2O1.9 (SDC) exhibited highest CO2 flux and long-term stability and was chosen as ceramic support for membrane performance improvement. Porous SDC layers were co-pressed on base supports using SDC and BYS powder mixtures which provided better sintering comparability and carbonate non-wettability. Thin SDC-carbonate dual-phase membrane (d-SDC/SDC60BYS40) of 150 μm thick was synthesized on SDC60BYS40. CO2 permeation flux for d-SDC/SDC60BYS40 exhibited increasing dependence on temperature and partial pressure gradient. The flux was higher than other SDC-based dual-phase membranes. Reducing membrane thickness proves effective to increase CO2 permeation flux for the dual-phase membrane.
ContributorsLu, Bo (Author) / Lin, Yuesheng (Thesis advisor) / Crozier, Peter (Committee member) / Herrmann, Macus (Committee member) / Forzani, Erica (Committee member) / Lind, Mary Laura (Committee member) / Arizona State University (Publisher)
Created2014
Description
Learning by trial-and-error requires retrospective information that whether a past action resulted in a rewarded outcome. Previous outcome in turn may provide information to guide future behavioral adjustment. But the specific contribution of this information to learning a task and the neural representations during the trial-and-error learning process is not well understood. In this dissertation, such learning is analyzed by means of single unit neural recordings in the rats' motor agranular medial (AGm) and agranular lateral (AGl) while the rats learned to perform a directional choice task. Multichannel chronic recordings using implanted microelectrodes in the rat's brain were essential to this study. Also for fundamental scientific investigations in general and for some applications such as brain machine interface, the recorded neural waveforms need to be analyzed first to identify neural action potentials as basic computing units. Prior to analyzing and modeling the recorded neural signals, this dissertation proposes an advanced spike sorting system, the M-Sorter, to extract the action potentials from raw neural waveforms. The M-Sorter shows better or comparable performance compared with two other popular spike sorters under automatic mode. With the sorted action potentials in place, neuronal activity in the AGm and AGl areas in rats during learning of a directional choice task is examined. Systematic analyses suggest that rat's neural activity in AGm and AGl was modulated by previous trial outcomes during learning. Single unit based neural dynamics during task learning are described in detail in the dissertation. Furthermore, the differences in neural modulation between fast and slow learning rats were compared. The results show that the level of neural modulation of previous trial outcome is different in fast and slow learning rats which may in turn suggest an important role of previous trial outcome encoding in learning.
ContributorsYuan, Yu'an (Author) / Si, Jennie (Thesis advisor) / Buneo, Christopher (Committee member) / Santello, Marco (Committee member) / Chae, Junseok (Committee member) / Arizona State University (Publisher)
Created2014
Description
To uncover the neural correlates to go-directed behavior, single unit action potentials are considered fundamental computing units and have been examined by different analytical methodologies under a broad set of hypotheses. Using a behaving rat performing a directional choice learning task, we aim to study changes in rat's cortical neural patterns while he improved his task performance accuracy from chance to 80% or higher. Specifically, simultaneous multi-channel single unit neural recordings from the rat's agranular medial (AGm) and Agranular lateral (AGl) cortices were analyzed using joint peristimulus time histogram (JPSTHs), which effectively unveils firing coincidences in neural action potentials. My results based on data from six rats revealed that coincidences of pair-wise neural action potentials are higher when rats were performing the task than they were not at the learning stage, and this trend abated after the rats learned the task. Another finding is that the coincidences at the learning stage are stronger than that when the rats learned the task especially when they were performing the task. Therefore, this coincidence measure is the highest when the rats were performing the task at the learning stage. This may suggest that neural coincidences play a role in the coordination and communication among populations of neurons engaged in a purposeful act. Additionally, attention and working memory may have contributed to the modulation of neural coincidences during the designed task.
ContributorsCheng, Bing (Author) / Si, Jennie (Thesis advisor) / Chae, Junseok (Committee member) / Seo, Jae-Sun (Committee member) / Arizona State University (Publisher)
Created2014
Description
A new photocatalytic material was synthesized to investigate its performance for the photoreduction of carbon dioxide (CO2) in the presence of water vapor (H2O) to valuable products such as carbon monoxide (CO) and methane (CH4). The performance was studied using a gas chromatograph (GC) with a flame ionization detector (FID) and a thermal conductivity detector (TCD). The new photocatalytic material was an ionic liquid functionalized reduced graphite oxide (IL-RGO (high conductive surface))-TiO2 (photocatalyst) nanocomposite. Brunauer-Emmett-Teller (BET), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and UV-vis absorption spectroscopy techniques were employed to characterize the new catalyst. In the series of experiments performed, the nanocomposite material was confined in a UV-quartz batch reactor, exposed to CO2 and H2O and illuminated by UV light. The primary product formed was CO with a maximum production ranging from 0.18-1.02 µmol(gcatalyst-hour)-1 for TiO2 and 0.41-1.41 µmol(gcatalyst-hour)-1 for IL-RGO-TiO2. A trace amount of CH4 was also formed with its maximum ranging from 0.009-0.01 µmol(gcatalyst-hour)-1 for TiO2 and 0.01-0.04 µmol(gcatalyst-hour)-1 for IL-RGO-TiO2. A series of background experiments were conducted and results showed that; (a) the use of a ionic liquid functionalized reduced graphite oxide -TiO2 produced more products as compared to commercial TiO2, (b) the addition of methanol as a hole scavenger boosted the production of CO but not CH4, (c) a higher and lower reduction time of IL-RGO as compared to the usual 24 hours of reduction presented basically the same production of CO and CH4, (d) the positive effect of having an ionic liquid was demonstrated by the double production of CO obtained for IL-RGO-TiO2 as compared to RGO-TiO2 and (e) a change in the amount of IL-RGO in the IL-RGO-TiO2 represented a small difference in the CO production but not in the CH4 production. This work ultimately demonstrated the huge potential of the utility of a UV-responsive ionic liquid functionalized reduced graphite oxide-TiO2 nano-composite for the reduction of CO2 in the presence of H2O for the production of fuels.
ContributorsCastañeda Flores, Alejandro (Author) / Andino, Jean M (Thesis advisor) / Forzani, Erica (Committee member) / Torres, Cesar (Committee member) / Arizona State University (Publisher)
Created2014
Description
The ability to monitor electrophysiological signals from the sentient brain is requisite to decipher its enormously complex workings and initiate remedial solutions for the vast amount of neurologically-based disorders. Despite immense advancements in creating a variety of instruments to record signals from the brain, the translation of such neurorecording instrumentation to real clinical domains places heavy demands on their safety and reliability, both of which are not entirely portrayed by presently existing implantable recording solutions. In an attempt to lower these barriers, alternative wireless radar backscattering techniques are proposed to render the technical burdens of the implant chip to entirely passive neurorecording processes that transpire in the absence of formal integrated power sources or powering schemes along with any active circuitry. These radar-like wireless backscattering mechanisms are used to conceive of fully passive neurorecording operations of an implantable microsystem. The fully passive device potentially manifests inherent advantages over current wireless implantable and wired recording systems: negligible heat dissipation to reduce risks of brain tissue damage and minimal circuitry for long term reliability as a chronic implant. Fully passive neurorecording operations are realized via intrinsic nonlinear mixing properties of the varactor diode. These mixing and recording operations are directly activated by wirelessly interrogating the fully passive device with a microwave carrier signal. This fundamental carrier signal, acquired by the implant antenna, mixes through the varactor diode along with the internal targeted neuropotential brain signals to produce higher frequency harmonics containing the targeted neuropotential signals. These harmonics are backscattered wirelessly to the external interrogator that retrieves and recovers the original neuropotential brain signal. The passive approach removes the need for internal power sources and may alleviate heat trauma and reliability issues that limit practical implementation of existing implantable neurorecorders.
ContributorsSchwerdt, Helen N (Author) / Chae, Junseok (Thesis advisor) / Miranda, Félix A. (Committee member) / Phillips, Stephen (Committee member) / Towe, Bruce C (Committee member) / Balanis, Constantine A (Committee member) / Frakes, David (Committee member) / Arizona State University (Publisher)
Created2014
Description
Control engineering offers a systematic and efficient approach to optimizing the effectiveness of individually tailored treatment and prevention policies, also known as adaptive or ``just-in-time'' behavioral interventions. These types of interventions represent promising strategies for addressing many significant public health concerns. This dissertation explores the development of decision algorithms for adaptive sequential behavioral interventions using dynamical systems modeling, control engineering principles and formal optimization methods. A novel gestational weight gain (GWG) intervention involving multiple intervention components and featuring a pre-defined, clinically relevant set of sequence rules serves as an excellent example of a sequential behavioral intervention; it is examined in detail in this research.
A comprehensive dynamical systems model for the GWG behavioral interventions is developed, which demonstrates how to integrate a mechanistic energy balance model with dynamical formulations of behavioral models, such as the Theory of Planned Behavior and self-regulation. Self-regulation is further improved with different advanced controller formulations. These model-based controller approaches enable the user to have significant flexibility in describing a participant's self-regulatory behavior through the tuning of controller adjustable parameters. The dynamic simulation model demonstrates proof of concept for how self-regulation and adaptive interventions influence GWG, how intra-individual and inter-individual variability play a critical role in determining intervention outcomes, and the evaluation of decision rules.
Furthermore, a novel intervention decision paradigm using Hybrid Model Predictive Control framework is developed to generate sequential decision policies in the closed-loop. Clinical considerations are systematically taken into account through a user-specified dosage sequence table corresponding to the sequence rules, constraints enforcing the adjustment of one input at a time, and a switching time strategy accounting for the difference in frequency between intervention decision points and sampling intervals. Simulation studies illustrate the potential usefulness of the intervention framework.
The final part of the dissertation presents a model scheduling strategy relying on gain-scheduling to address nonlinearities in the model, and a cascade filter design for dual-rate control system is introduced to address scenarios with variable sampling rates. These extensions are important for addressing real-life scenarios in the GWG intervention.
A comprehensive dynamical systems model for the GWG behavioral interventions is developed, which demonstrates how to integrate a mechanistic energy balance model with dynamical formulations of behavioral models, such as the Theory of Planned Behavior and self-regulation. Self-regulation is further improved with different advanced controller formulations. These model-based controller approaches enable the user to have significant flexibility in describing a participant's self-regulatory behavior through the tuning of controller adjustable parameters. The dynamic simulation model demonstrates proof of concept for how self-regulation and adaptive interventions influence GWG, how intra-individual and inter-individual variability play a critical role in determining intervention outcomes, and the evaluation of decision rules.
Furthermore, a novel intervention decision paradigm using Hybrid Model Predictive Control framework is developed to generate sequential decision policies in the closed-loop. Clinical considerations are systematically taken into account through a user-specified dosage sequence table corresponding to the sequence rules, constraints enforcing the adjustment of one input at a time, and a switching time strategy accounting for the difference in frequency between intervention decision points and sampling intervals. Simulation studies illustrate the potential usefulness of the intervention framework.
The final part of the dissertation presents a model scheduling strategy relying on gain-scheduling to address nonlinearities in the model, and a cascade filter design for dual-rate control system is introduced to address scenarios with variable sampling rates. These extensions are important for addressing real-life scenarios in the GWG intervention.
ContributorsDong, Yuwen (Author) / Rivera, Daniel E (Thesis advisor) / Dai, Lenore (Committee member) / Forzani, Erica (Committee member) / Rege, Kaushal (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2014